Hallie - Script :)

2021-08-37_LoopsAndFunctions.R

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+#######################################
+# Examples of loops and functions in R
+# 2021-08-27
+# Hallie Eilerts
+# hallie.eilerts@lshtm.ac.uk
+#######################################
+
+
+# Loops  -----------------------------------------------
+
+x <- c(2,5,3,9,8,11,6)
+y <- c()
+
+for(i in 1:length(x)){
+  y[i] <- x[i] + x[i+1]
+}
+y
+
+
+y <- c()
+for(i in 1:(length(x)-1)){
+  y[i] <- x[i] + x[i+1]
+}
+y
+
+# Below example borrowed from:
+# https://www.datamentor.io/r-programming/for-loop/
+x <- c(2,5,3,9,8,11,6)
+count <- 0
+for(i in x) {
+  if(i %% 2 == 0){ # check remainder. if 0, go to next step
+    count = count+1
+    }
+}
+count
+
+
+x <- c(2,4,4,9,8,12,6)
+count <- 0
+for(i in x) {
+  if(i %% 2 == 0){
+    count = count+1
+    }
+}
+count
+
+
+x <- c(2,4,4,9,8,12,6)
+total1 <- 0
+total2 <- 0
+for(j in x) {
+
+  if(j %% 2 == 0){ 
+    total1 = total1 + j
+  }
+  if(j %% 2 != 0){ 
+    total2 = total2 + j
+  }
+
+}
+total1
+total2
+
+
+# Functions ---------------------------------------------------------------
+
+fn.whatever <- function(x,y){x+y}
+fn.whatever(3,4)
+
+fn.whatever <- function(x){x^2}
+fn.whatever(5)
+
+fn.function2 <- function(x){ x / sum(x)}
+v.somenumbers <- c(2,4,4,9,8,12,6)
+fn.function2(v.somenumbers)
+
+
+# Count even numbers
+fn.function3 <- function(x) {
+  v.evennumbers <- subset(x, x %% 2 == 0)
+  length(v.evennumbers)
+}
+
+v.somenumbers <- c(2,4,4,9,8,12,6)
+fn.function3(v.somenumbers)
+
+
+# Car data ----------------------------------------------------------------
+
+head(mtcars)
+
+# Create column for car name
+mtcars$car <- row.names(mtcars)
+row.names(mtcars) <- NULL
+
+# Separate Valiant from other cars
+valiant <- subset(mtcars, car == "Valiant")
+othercars <- subset(mtcars, car != "Valiant")
+
+# Compare valiant with other cars to find which is most similar
+othercars$samegear <- NA
+othercars$wtdif <- NA
+for(i in 1:nrow(othercars)){
+
+  othercars[i,"samegear"] <- othercars[i,"gear"] == valiant$gear
+  othercars[i,"wtdif"] <- abs(othercars[i,"wt"] - valiant$wt)
+}
+subset(othercars, samegear == TRUE)
+subset(othercars, samegear == TRUE & wtdif == min(othercars$wtdif))
+
+
+# Create new columns named loop
+othercars <- subset(mtcars, car != "Valiant")
+for(i in (ncol(othercars)+1):(ncol(othercars)+5)){
+  othercars <- cbind(othercars, i)
+  names(othercars)[i] <- paste("loop",i, sep="")
+}
+head(othercars)
+
+
+# Australia data -------------------------------------------------------
+
+
+# quarterly time series of the number of Australian residents from 1971 to 1993
+install.packages("astsa")
+library(astsa)
+
+# Prepare data
+data <- matrix(c(NA,austres,NA),ncol = 4,byrow=TRUE )
+df.data <- data.frame(data)
+names(df.data) <- c("Qtr1","Qtr2","Qtr3","Qtr4")
+
+# 3 different ways to calculate row totals
+
+### By hand
+df.data$AnnualTotal <- df.data$Qtr1 + df.data$Qtr2 + df.data$Qtr3 + df.data$Qtr4
+df.data$AnnualTotal <- NULL
+
+### Loop
+for(i in 1:nrow(df.data)){
+  df.data$AnnualTotal[i,] <- sum(df.data[i,], na.rm = T)
+}
+head(df.data)
+df.data$AnnualTotal <- NULL
+
+### Vectorize
+df.data$AnnualTotal <- apply(df.data, 1, sum, na.rm=T) # the 1 is telling apply to perform the action on the rows. if you used 2, it would apply to columns.
+df.data
+
+
+# DHS data ---------------------------------------------------------------------
+
+# Adapted from:
+# https://github.com/mrc-ide/demogsurv/blob/master/vignettes/rdhs-integration.md
+
+
+#devtools::install_github("ropensci/rdhs", ref = "issue33_path")
+library(rdhs)
+library(demogsurv)
+library(ggplot2)
+library(data.table)
+library(haven)
+
+# Download the DHS data
+
+## First create an account at the DHS website
+
+## Enter your credentials here
+set_rdhs_config(email = "youremail@email.com",
+                password_prompt =  TRUE,
+                project = "Your DHS project name", 
+                config_path = "rdhs.json",
+                global=FALSE)
+
+# we will give our permission here so that we don't have to provide a prompt within the README.
+Sys.setenv("rdhs_RENVIRON_PERMISSION"=1)
+
+## a little nugget to return API requests as data.table rather than data.frame.
+Sys.setenv(rdhs_DATA_TABLE = "TRUE")
+
+## Look at available countries
+countries <- dhs_countries()
+countries$DHS_CountryCode
+
+## Make vector with countries of interest
+cc <- c("MZ", "TZ", "UG")
+
+# Use rdhs to retreive datasets, downloading them from DHS website if not already in the rdhs cache.
+surveys <- dhs_surveys(countryIds = cc, surveyYearStart=1990, surveyType = "DHS")
+
+# Identify births recode (BR) datasets corresponding to these surveys.
+step <- dhs_datasets(fileType = "IR", fileFormat = "flat")
+ird <- step[which(step$SurveyId %in% surveys$SurveyId),]
+
+# Use rdhs to retreive datasets, downloading them from DHS website if not already in the rdhs cache.
+Sys.setenv("rdhs_LOUD_DOWNLOAD" = TRUE)
+ird$path <- unlist(get_datasets(ird$FileName)) #  clear_cache = TRUE )) 
+
+# Load all of the datasets into R as a list.
+ir <- list()
+for(survid in ird$SurveyId){
+  print(survid)
+  dat <- readRDS(ird[which(ird$SurveyId == survid),]$path)
+  dat <- dat[grep("caseid|^v0|^v1|^b", names(dat))]
+  ir[[survid]] <- dat
+}
+
+ir <- lapply(ir, haven::as_factor)
+
+## Add survey-level variables
+ir <- Map(data.frame,
+          SurveyId = surveys$SurveyId,
+          CountryName = surveys$CountryName,
+          SurveyYear = surveys$SurveyYear,
+          ir)
+
+
+#### Some functions
+
+
+length(ir)
+names(ir)
+head(ir$MZ1997DHS)
+lapply(ir, function(x) head(x))
+
+ldply(ir, function(x){ x <- x[,c("CountryName","v024")]
+                       x <- x[!duplicated(x),];
+                       return(x)})
+
+l.data <- lapply(ir, function(x){ x <- x[,c("SurveyId","CountryName","v024")]
+                                  x <- x[!duplicated(x),];
+                                  return(x)})
+mynames <- c("Survey","Country","Region")
+l.data <- lapply(l.data, setNames, mynames)
+head(l.data$MZ1997DHS)
+
+#### Loops
+
+l.regioncount <- c()
+for(i in 1:length(ir)){
+  l.regioncount[[i]] <- setDT(ir[[i]])[,.N,by=v024]
+}
+l.regioncount
+names(l.regioncount) <- names(ir)
+
+

R-resources

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+
+
+##List of useful R packages
+
+Feel free to add as much as you want 
+
+#IMPORTING DATA
+
+
+- haven package: read and write SPSS flies
+https://haven.tidyverse.org/reference/read_spss.html
+
+- readxl package: read excel files
+https://readxl.tidyverse.org/
+
+- tabulizer package: import pdf files
+https://cran.r-project.org/web/packages/tabulizer/vignettes/tabulizer.html
+
+
+#TIDYING AND MANIPULATING DATA
+
+- tidyr package: cleaning data (general package from tidyverse)
+https://github.com/tidyverse/tidyr
+
+
+- tidyxl package: cleaning very untidy excel files (including colours and font format)
+https://cran.r-project.org/web/packages/tidyxl/vignettes/tidyxl.html
+
+Blog post:
+https://www.r-bloggers.com/2018/05/tidying-messy-excel-data-tidyxl/
+https://rdrr.io/cran/tidyxl/f/vignettes/tidyxl.Rmd
+
+YouTube tutorial: 
+https://www.youtube.com/watch?v=1sinC7wsS5U
+
+- staplr package: manipulating pdf in r (i.e., rotating pdf, merging pdf)
+https://cran.r-project.org/web/packages/staplr/staplr.pdf